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首页> 外文期刊>Journal of Molecular Biology >Induction and relaxation dynamics of the regulatory network controlling the type III secretion system encoded within Salmonella Pathogenicity Island 1
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Induction and relaxation dynamics of the regulatory network controlling the type III secretion system encoded within Salmonella Pathogenicity Island 1

机译：沙门氏菌致病岛1中编码的III型分泌系统的调控网络的诱导和松弛动力学

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摘要

Bacterial pathogenesis requires the precise spatial and temporal control of gene expression, the dynamics of which are controlled by regulatory networks. A network encoded within Salmonella Pathogenicity Island 1 controls the expression of a type III protein secretion system involved in the invasion of host cells. The dynamics of this network are measured in single cells using promoter-green fluorescent protein (gfp) reporters and flow cytometry. During induction, there is a temporal order of gene expression, with transcriptional inputs turning on first, followed by structural and effector genes. The promoters show varying stochastic properties, where graded inputs are converted into all-or-none and hybrid responses. The relaxation dynamics are measured by shifting cells from inducing to noninducing conditions and by measuring fluorescence decay. The gfp expressed from promoters controlling the transcriptional inputs (hilC and hilD) and structural genes (prgH) decay exponentially, with a characteristic time of 50-55 min. In contrast, the gfp expressed from a promoter controlling the expression of effectors (sicA) persists for 110 +/- 9 min. This promoter is controlled by a genetic circuit, formed by a transcription factor (InvF), a chaperone (SicA), and a secreted protein (SipC), that regulates effector expression in response to the secretion capacity of the cell. A mathematical model of this circuit demonstrates that the delay is due to a split positive feedback loop. This model is tested in a Delta sicA knockout strain, where sicA is complemented with and without the feedback loop. The delay is eliminated when the feedback loop is deleted. Furthermore, a robustness analysis of the model predicts that the delay time can be tuned by changing the affinity of SicA:InvF multimers for an operator in the sicA promoter. This prediction is used to construct a targeted library, which contains mutants with both longer and shorter delays. This combination of theory and experiments provides a platform for predicting how genetic perturbations lead to changes in the global dynamics of a regulatory network.
机译：细菌的发病机理需要对基因表达进行精确的时空控制，其动态由调控网络控制。沙门氏菌致病岛1中编码的网络控制参与宿主细胞入侵的III型蛋白质分泌系统的表达。使用启动子绿色荧光蛋白（gfp）报告基因和流式细胞仪在单个细胞中测量该网络的动力学。在诱导过程中，存在基因表达的时间顺序，首先打开转录输入，然后是结构和效应基因。启动子显示出不同的随机性，其中分级输入被转换为全或无和混合响应。通过将细胞从诱导条件转变为非诱导条件并通过测量荧光衰减来测量弛豫动力学。从控制转录输入（hilC和hilD）和结构基因（prgH）的启动子表达的gfp呈指数衰减，特征时间为50-55分钟。相反，从控制效应子（sicA）表达的启动子表达的gfp持续110 +/- 9分钟。该启动子受由转录因子（InvF），分子伴侣（SicA）和分泌蛋白（SipC）形成的遗传回路控制，该基因回路响应细胞的分泌能力来调节效应子的表达。该电路的数学模型表明，延迟是由于正反馈环路的分裂引起的。该模型在Delta sicA敲除菌株中进行了测试，其中sicA带有或不带有反馈回路。删除反馈回路后，将消除延迟。此外，模型的鲁棒性分析预测可以通过更改SicA：InvF多聚体对sicA启动子中的操纵子的亲和力来调节延迟时间。该预测用于构建目标文库，该文库包含具有较长和较短延迟的突变体。理论和实验的结合为预测遗传扰动如何导致监管网络的全球动态变化提供了一个平台。

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